Collaborative Swarm Shape Reconstruction of Tumbling Space Targets via Decentralized Dynamic Factor Graph Optimization

Abstract

On-orbit servicing (OOS) has become an essential aspect of modern space missions, encompassing satellite maintenance, orbital assembly, and debris removal. This paper presents a novel decentralized navigation algorithm designed for a swarm of servicing spacecraft to collaboratively reconstruct the shape of unknown tumbling space objects. The proposed method leverages a dynamic factor graph-based Collaborative Simultaneous Localization and Mapping (C-SLAM) framework, integrating observed and identified point cloud features across the swarm. To address the challenges associated with the target’s tumbling dynamics, the approach also incorporates a dynamic SLAM formulation, utilizing a noisy parametric model to propagate the dynamic map and construct the dynamic factor graph at the front-end. Kinematic factors are introduced to account for loop closures, enabling the swarm to recognize previously observed features as they rotate with the target, thereby enhancing mapping robustness. Additionally, the target kinematic model parameters themselves—such as its center of mass, linear velocity, and angular velocity—are estimated in real time from the reconstructed maps. The latter notably is estimated using a singular value decomposition approach that determine the best fit rotation between two consecutive sets of mapped points. These estimates are fed back into the kinematic factors and loop closure processes to refine map optimization iteratively. Simulation results demonstrate that incorporating kinematic factors, addressing loop closures, and facilitating inter-robot communication significantly enhance the swarm’s ability to track the evolving map without a central leader. This decentralized approach highlights the potential of equipping spacecraft swarms with advanced, robust, and scalable perception capabilities for the collaborative inspection and characterization of unknown tumbling space targets.